Performance Analysis of Licensed-Assisted Access with Listen-Before-Talk in Non-Saturated Condition

Title
Performance Analysis of Licensed-Assisted Access with Listen-Before-Talk in Non-Saturated Condition
Author(s)
김용재; 송유재; Rumin Yang; 한영남
KIOST Author(s)
Song, Yujae(송유재)
Publication Year
2017-08-23
Abstract
This paper analyzes the performance of licensedassistedaccess (LAA) systems conditioned on non-saturatedtraffic in unlicensed spectrum. Under the condition, we proposeMarkov chain models which describe time-domain behavior of aLAA system with different listen-before-talk (LBT) procedures.For evaluation of coexistence performance, a Wi-Fi access pointmodel is adopted and combined with the proposed models.We find an optimal contention window (CW) size of the LAAsystems in which total throughput of both networks is maximizedwhile satisfying the required throughput of each network, underthe given traffic densities of both networks. Total throughputimprovement is compared according to different LBT procedures.Numerical results show that the LAA systems with the optimalCW size lead to higher throughput improvement than withoutthe optimal CW in the coexistence scenario.ystem with different listen-before-talk (LBT) procedures.For evaluation of coexistence performance, a Wi-Fi access pointmodel is adopted and combined with the proposed models.We find an optimal contention window (CW) size of the LAAsystems in which total throughput of both networks is maximizedwhile satisfying the required throughput of each network, underthe given traffic densities of both networks. Total throughputimprovement is compared according to different LBT procedures.Numerical results show that the LAA systems with the optimalCW size lead to higher throughput improvement than withoutthe optimal CW in the coexistence scenario.
URI
https://sciwatch.kiost.ac.kr/handle/2020.kiost/23868
Bibliographic Citation
Asia Pacific Wireless Communications Symposium (APWCS), pp.1 - 5, 2017
Publisher
IEEE
Type
Conference
Language
English
Publisher
IEEE
Related Researcher
Research Interests

Maritime 5G and B5G,Maritime IoT,Deep reinforcement learning and its maritime applications,차세대 해양통신,해양 IoT,심층강화학습 및 해양통신 적용

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